Proceedings ArticleDOI
DOES multispectral / hyperspectral pansharpening improve the performance of anomaly detection?
Ying Qu,Hairong Qi,Bulent Ayhan,Chiman Kwan,R. Kidd +4 more
- pp 6130-6133
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TLDR
Experimental results show that, performing anomaly detection on high resolution images improves the detection rate, and at the mean time suppresses the false alarm rate.Abstract:
Pansharpening refers to the fusion of a high spatial resolution panchromatic image with high spectral resolution multispectral or hyperspectral images (MSI or HSI) to yield high resolution data in both spectral and spatial domains. It has been widely adopted as a primary preprocessing step for numerous applications. In this paper, we perform a literature survey of various pansharpening algorithms including the most advanced deep learning approaches for both multispectral and hyperspectral images. We further evaluate the effect of the resolution difference on anomaly detection. Synthetic multispectral and hyperspectral images are generated to evaluate the performance of anomaly detection on high resolution images. Eight state-of-the-art MSI and HSI pansharpening methods are compared in this paper. Experimental results show that, performing anomaly detection on high resolution images improves the detection rate, and at the mean time suppresses the false alarm rate.read more
Citations
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Journal ArticleDOI
Deep Hyperspectral Image Sharpening
TL;DR: A deep HSI sharpening method is presented for the fusion of an LR-HSI with an HR-MSI, which directly learns the image priors via deep convolutional neural network-based residual learning.
Journal ArticleDOI
Regularizing Hyperspectral and Multispectral Image Fusion by CNN Denoiser
TL;DR: A novel HSI and MSI fusion method based on the subspace representation and convolutional neural network (CNN) denoiser, i.e., a well-trained CNN for gray image denoising, which has superior performance over the state-of-the-art fusion methods.
Journal ArticleDOI
A New Benchmark Based on Recent Advances in Multispectral Pansharpening: Revisiting Pansharpening With Classical and Emerging Pansharpening Methods
Gemine Vivone,Mauro Dalla Mura,Andrea Garzelli,Rocco Restaino,Giuseppe Scarpa,Magnus O. Ulfarsson,Luciano Alparone,Jocelyn Chanussot +7 more
TL;DR: A new benchmark consisting of recent advances in MS pansharpening is proposed, and optimized classical approaches [multiresolution analysis (MRA) and component substitution (CS)] are compared with methods belonging to the third generation of panshARPening, represented by variational optimization-based (VO) and machine learning (ML) techniques.
Journal ArticleDOI
Recent advances and new guidelines on hyperspectral and multispectral image fusion
TL;DR: This work gives a comprehensive review and new guidelines for HSI-MSI fusion, categorized as four categories, including pan-sharpening based approaches, matrix factorizationbased approaches, tensor representation Based approaches, and deep convolution neural network based approaches.
Journal ArticleDOI
A Novel Utilization of Image Registration Techniques to Process Mastcam Images in Mars Rover With Applications to Image Fusion, Pixel Clustering, and Anomaly Detection
TL;DR: A two-step image alignment approach with a novel utilization of existing image registration algorithms is introduced in this paper and is applied to a set of Mastcam stereo images, demonstrating that the fused images can improve pixel clustering and anomaly detection performance.
References
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Journal ArticleDOI
A Critical Comparison Among Pansharpening Algorithms
Gemine Vivone,Luciano Alparone,Jocelyn Chanussot,Mauro Dalla Mura,Andrea Garzelli,Giorgio Licciardi,Rocco Restaino,Lucien Wald +7 more
TL;DR: The authors attempt to fill the gap by providing a critical description and extensive comparisons of some of the main state-of-the-art pansharpening methods by offering a detailed comparison of their performances with respect to the different instruments.
Journal ArticleDOI
Coupled Nonnegative Matrix Factorization Unmixing for Hyperspectral and Multispectral Data Fusion
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